deepspeedai / deepspeedai/DeepSpeed
[REQUEST] Saving model weights only in checkpoints
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Description
Currently, in ZeRO-3, we are saving model params and optimizer states together in .*_optim_state.pt files. Saving optimzier states may greatly increase the checkpoint size, while we don't actually needs them for inference.
In order to extract the model weights, we need to load all checkpoint shards into memory, then extract the weights out, which requires a huge amount of RAM.
Therefore, it would be great to enable only saving model weights in checkpoints.
### Tasks
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by tracing the ZeRO-3 checkpoint save path that produces *_optim_state.pt files and identify where model parameters and optimizer states are combined. Done means checkpoints can contain only model weights, and extracting those weights no longer requires loading optimizer states or all shards into memory.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- distributed-systems, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100